Spectral Profiles, a Novel Representation of Tandem Mass Spectra and Their Applications for de Novo Peptide Sequencing and Identification

peer-reviewed · Molecular & Cellular Proteomics · 2009

peer-reviewed · Molecular & Cellular Proteomics · 2009. Sangtae Kim et al. Despite many efforts in the last decade, the progress in de novo peptide sequencing has been slow with only…
Date 2009-06-01
Type peer-reviewed
Venue Molecular & Cellular Proteomics
Publisher Elsevier BV
Contribution algorithm
DOI 10.1074/mcp.M800535-MCP200
Citations (OpenAlex) 37
Venue 2-year citedness 4.69

Abstract

Despite many efforts in the last decade, the progress in de novo peptide sequencing has been slow with only 30-45% of all peptides correctly reconstructed. We argue that accurate full-length peptide sequencing may be an unattainable goal for some spectra and demonstrate how to accurately sequence gapped peptides instead. We further argue that gapped peptides are nearly as useful as full-length peptides for error-tolerant database searches. Gapped peptides occupy a niche between long but inaccurate full-length reconstructions and short but accurate peptide sequence tags. Our MS-Profile tool uses spectral profiles, a new representation of tandem mass spectra, to generate gapped peptides that are longer and more accurate than peptide sequence tags of length 3 traditionally used to speed up database searches in proteomics. In addition, spectral profiles also enable intuitive visualization of all high scoring de novo reconstructions of tandem mass spectra.

Authors

  1. Sangtae Kim · University of California San Diego
  2. Nuno Bandeira · University of California San Diego, University of California System
  3. Pavel A. Pevzner · Max Planck Institute of Molecular Cell Biology and Genetics, Saint Petersburg Academic University, St Petersburg University, St. Petersburg State University, University of California San Diego, University of Southern California

Methods and tools

  • MS-Profile: Spectral profile representation for gapped de novo peptide sequencing and identification.

Cites (15)

Cited by (13)

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